This one-day workshop aims to increase participants understanding of the principles, methods, and interpretation of regression models using the R software environment, a powerful, popular and free statistical and graphical programming language.
QFAB’s chemi-biology computational platform brings together complementary expertise in infectious disease research and advanced computational methods to accelerate the drug discovery process. The platform aims at increasing the likelihood of discovering successful lead compounds for anti-infective medicine. Unique in Australia, the platform consist of high-performance hardware and an integrated suite of open source and commercial software linked to curated chemical and biological datasets. The platform offers an environment for collaborative research, enabling sharing of workflows and computational tools tailored for lead compound discovery in infectious diseases through four main technical objectives:
- Access to large shared collections of compounds, assays and knowledge
- Access to computational tools that can be tailored for lead compound discovery in infectious diseases
- A systems biology approach to infectious diseases drug discovery
- Sharing specialised analytical workflows
The Platform builds on, and integrates with, QFAB’s Systems Biology Platform. More information about the hardware, software and data accessible through the platform is available on the dedicated Systems Biology Platform portal.
This Computational Platform is supported by the Australian Research Council’s Linkage Infrastructure, Equipment and Facilities funding scheme:
- LE0989334, An integrated high-performance computational platform powering systems biology investigation, CIs-Ragan, Grimmond, Muscat, Teasdale, Barker, Gorse, Wells and Little
- LE120100071, Chemi–Biology Computational Platform for Lead Discovery in Infectious Disease, CIs-Ragan, Cooper, Capon, Gorse, Stoermer, Camp, Andrews, Hofmann, Kurtboke, Huston, Timms